Seismic exploration, whether on land or at sea, is a method of detecting geologic structures below the surface of the earth by analyzing seismic energy that has interacted with the geologic structures. A seismic energy source generates a seismic signal that propagates into the earth, where the signal may be partially reflected, refracted, diffracted, and/or otherwise affected by one or more geologic structures such as, for example, interfaces between underground formations having varying acoustic impedances. Seismic receivers placed at or near the earth's surface, within bodies of water, or below the earth's surface in well-bores are able to detect the affected seismic signal and record it. The recordings are processed to generate information about the location and physical properties of the subsurface geologic structures that interacted with the seismic signal.
A set of recordings taken during a particular time period may be referred to as a “survey.” One or more signals recorded from a single survey may be used to generate an image of the subsurface formations. Such images, referred to as “3D images,” indicate the state of the subsurface formations during the time period in which the survey was taken. Multiple realizations of 3D images can also be generated. As used herein, “realizations” may refer to different 3D images generated from the same survey. Different realizations can be prepared, for example, from “up-going” and “down-going” wavefields, which result from the same wavefront arriving at the receivers from different directions (e.g., before and after reflecting off of a nearby surface). Different realizations can also be generated from different selections of traces or from different processing of the same traces.
Seismic data can be gathered at different times to facilitate “time-lapse” or “4D” imaging. 4D processing of two seismic datasets recorded at different times can be used to determine how and where the Earth's properties have changed. For example, 3D images from surveys taken at different times can be compared to generate “4D images,” which are also referred to as “4D differences.” The earlier survey is referred to as the “baseline” survey, and the later survey is referred to as the “monitor” survey. As used herein, “realizations” may also refer to different 4D images that are generated using one or more different realizations of 3D images. For example, where a baseline survey yields a baseline 3D image, and a monitor survey yields first and second monitor 3D images, a first 4D image can be generated by differencing the baseline 3D image and the first monitor 3D image, and a second 4D image can be generated by differencing the baseline 3D image and the second monitor 3D image. As another example, where a baseline survey yields first and second baseline 3D images, and a monitor survey yields first and second monitor 3D images, a first 4D image can be generated by differencing the first baseline 3D image and the first monitor 3D image, and a second 4D image can be generated by differencing the second baseline 3D image and the second monitor 3D image.
Because 4D images are generated from seismic data acquired at different times, 4D images measure changes in subsurface formations over time. For example, 4D images may be developed in an active reservoir before and after a period of production. Such 4D images are used to identify fluid movements, or changes in fluid or lithological properties in and around a reservoir. Features of a 4D image related to fluid production may be considered “4D signal,” while other unwanted elements of the image may be considered “4D noise.” Seismic recordings may be distorted by coherent or incoherent noise, and 3D images and 4D images may be distorted or otherwise rendered inaccurate by such noise. Noise in two different images is considered coherent when similar noise is present in equivalent portions of both images. In contrast, incoherent noise is present in one but not both images.
4D imaging is particularly difficult to accomplish when coherent noise is present in multiple images. For example, coherent noise can be present in both the up-going and down-going realizations from the monitor survey but not in the baseline survey. In this case, the coherent noise would show up in the 4D image generated from the up-going realizations as well as the 4D image generated from the down-going realizations. While comparing the 4D images may identify certain incoherent noise, the comparison would not identify this coherent noise because it is present in both 4D images. Accordingly, 4D noise, and coherent 4D noise in particular, interferes with the ability to clearly measure changes in subsurface formations over time using 4D imaging.